002f9879b2
Replaces cherry-picked upstream_ref with complete source trees. xllm/ — Iluvatar official C++ inference engine (15MB, 1470 files) Complete: kernels → layers → models → runtime → scheduler → api Excluded: .git, binary images, third_party submodule checkouts ds_vllm/ — Iluvatar official vllm fork (8MB, 703 files) Included: csrc/ (ALL CUDA kernels), fused_moe/, qwen3_5 model, _custom_ops Excluded: tests, benchmarks, docs, examples (not needed for reference) Critical call chains now fully traceable: MoE: moe_topk_softmax_kernels.cuh → ixformer.h → fused_moe.cpp → layer GDN: qwen3_gated_delta_net_base.cpp → qwen3_5_gated_delta_net.cpp Attention: ixformer.h → xllm_paged_attention → attention.cpp
60 lines
2.2 KiB
Plaintext
60 lines
2.2 KiB
Plaintext
// TODO: Remove this once ROCm upgrade to torch 2.11.
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#include <torch/all.h>
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#include <torch/cuda.h>
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#include <cuda_runtime.h>
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// This function assumes that `cpu_tensor` is a CPU tensor,
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// and that UVA (Unified Virtual Addressing) is enabled.
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torch::Tensor get_cuda_view_from_cpu_tensor(torch::Tensor& cpu_tensor) {
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TORCH_CHECK(cpu_tensor.device().is_cpu(), "Input tensor must be on CPU");
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// handle empty tensor
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if (cpu_tensor.numel() == 0) {
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return torch::empty(cpu_tensor.sizes(),
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cpu_tensor.options().device(torch::kCUDA));
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}
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if (cpu_tensor.is_pinned()) {
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// If CPU tensor is pinned, directly get the device pointer.
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void* host_ptr = const_cast<void*>(cpu_tensor.data_ptr());
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void* device_ptr = nullptr;
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cudaError_t err = cudaHostGetDevicePointer(&device_ptr, host_ptr, 0);
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TORCH_CHECK(err == cudaSuccess,
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"cudaHostGetDevicePointer failed: ", cudaGetErrorString(err));
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return torch::from_blob(
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device_ptr, cpu_tensor.sizes(), cpu_tensor.strides(),
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[base = cpu_tensor](void*) {}, // keep cpu tensor alive
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cpu_tensor.options().device(torch::kCUDA));
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}
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// If CPU tensor is not pinned, allocate a new pinned memory buffer.
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torch::Tensor contiguous_cpu = cpu_tensor.contiguous();
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size_t nbytes = contiguous_cpu.nbytes();
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void* host_ptr = nullptr;
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cudaError_t err = cudaHostAlloc(&host_ptr, nbytes, cudaHostAllocMapped);
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if (err != cudaSuccess) {
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AT_ERROR("cudaHostAlloc failed: ", cudaGetErrorString(err));
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}
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err = cudaMemcpy(host_ptr, contiguous_cpu.data_ptr(), nbytes,
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cudaMemcpyDefault);
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if (err != cudaSuccess) {
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cudaFreeHost(host_ptr);
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AT_ERROR("cudaMemcpy failed: ", cudaGetErrorString(err));
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}
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void* device_ptr = nullptr;
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err = cudaHostGetDevicePointer(&device_ptr, host_ptr, 0);
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if (err != cudaSuccess) {
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cudaFreeHost(host_ptr);
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AT_ERROR("cudaHostGetDevicePointer failed: ", cudaGetErrorString(err));
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}
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auto deleter = [host_ptr](void*) { cudaFreeHost(host_ptr); };
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return torch::from_blob(device_ptr, contiguous_cpu.sizes(),
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contiguous_cpu.strides(), deleter,
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contiguous_cpu.options().device(torch::kCUDA));
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} |